Class AbstractScalarDifferentiableOptimizer
- java.lang.Object
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- org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer<DifferentiableMultivariateFunction>
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- org.apache.commons.math3.optimization.general.AbstractScalarDifferentiableOptimizer
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- All Implemented Interfaces:
BaseMultivariateOptimizer<DifferentiableMultivariateFunction>
,BaseOptimizer<PointValuePair>
,DifferentiableMultivariateOptimizer
- Direct Known Subclasses:
NonLinearConjugateGradientOptimizer
@Deprecated public abstract class AbstractScalarDifferentiableOptimizer extends BaseAbstractMultivariateOptimizer<DifferentiableMultivariateFunction> implements DifferentiableMultivariateOptimizer
Deprecated.As of 3.1 (to be removed in 4.0).Base class for implementing optimizers for multivariate scalar differentiable functions. It contains boiler-plate code for dealing with gradient evaluation.- Since:
- 2.0
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Field Summary
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Fields inherited from class org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer
evaluations
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Constructor Summary
Constructors Modifier Constructor Description protected
AbstractScalarDifferentiableOptimizer()
Deprecated.protected
AbstractScalarDifferentiableOptimizer(ConvergenceChecker<PointValuePair> checker)
Deprecated.
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Method Summary
All Methods Instance Methods Concrete Methods Deprecated Methods Modifier and Type Method Description protected double[]
computeObjectiveGradient(double[] evaluationPoint)
Deprecated.Compute the gradient vector.PointValuePair
optimize(int maxEval, MultivariateDifferentiableFunction f, GoalType goalType, double[] startPoint)
Deprecated.Optimize an objective function.protected PointValuePair
optimizeInternal(int maxEval, DifferentiableMultivariateFunction f, GoalType goalType, double[] startPoint)
Deprecated.Optimize an objective function.-
Methods inherited from class org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer
computeObjectiveValue, doOptimize, getConvergenceChecker, getEvaluations, getGoalType, getLowerBound, getMaxEvaluations, getStartPoint, getUpperBound, optimize, optimize, optimizeInternal
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Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Methods inherited from interface org.apache.commons.math3.optimization.BaseMultivariateOptimizer
optimize
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Methods inherited from interface org.apache.commons.math3.optimization.BaseOptimizer
getConvergenceChecker, getEvaluations, getMaxEvaluations
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Constructor Detail
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AbstractScalarDifferentiableOptimizer
@Deprecated protected AbstractScalarDifferentiableOptimizer()
Deprecated.Simple constructor with default settings. The convergence check is set to aSimpleValueChecker
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AbstractScalarDifferentiableOptimizer
protected AbstractScalarDifferentiableOptimizer(ConvergenceChecker<PointValuePair> checker)
Deprecated.- Parameters:
checker
- Convergence checker.
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Method Detail
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computeObjectiveGradient
protected double[] computeObjectiveGradient(double[] evaluationPoint)
Deprecated.Compute the gradient vector.- Parameters:
evaluationPoint
- Point at which the gradient must be evaluated.- Returns:
- the gradient at the specified point.
- Throws:
TooManyEvaluationsException
- if the allowed number of evaluations is exceeded.
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optimizeInternal
protected PointValuePair optimizeInternal(int maxEval, DifferentiableMultivariateFunction f, GoalType goalType, double[] startPoint)
Deprecated.Optimize an objective function.- Overrides:
optimizeInternal
in classBaseAbstractMultivariateOptimizer<DifferentiableMultivariateFunction>
- Parameters:
maxEval
- Maximum number of function evaluations.f
- Objective function.goalType
- Type of optimization goal: eitherGoalType.MAXIMIZE
orGoalType.MINIMIZE
.startPoint
- Start point for optimization.- Returns:
- the point/value pair giving the optimal value for objective function.
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optimize
public PointValuePair optimize(int maxEval, MultivariateDifferentiableFunction f, GoalType goalType, double[] startPoint)
Deprecated.Optimize an objective function.- Parameters:
f
- Objective function.goalType
- Type of optimization goal: eitherGoalType.MAXIMIZE
orGoalType.MINIMIZE
.startPoint
- Start point for optimization.maxEval
- Maximum number of function evaluations.- Returns:
- the point/value pair giving the optimal value for objective function.
- Throws:
DimensionMismatchException
- if the start point dimension is wrong.TooManyEvaluationsException
- if the maximal number of evaluations is exceeded.NullArgumentException
- if any argument isnull
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